The implantation of bioprosthetic heart valves (BHVs) is increasingly becoming the treatment of choice in patients requiring heart valve replacement surgery. Unlike mechanical heart valves, BHVs are less thrombogenic and exhibit superior hemodynamic properties. However, BHVs are prone to structural valve degeneration (SVD), an unavoidable condition limiting graft durability. Mechanisms underlying SVD are incompletely understood, and early concepts suggesting the purely degenerative nature of this process are now considered oversimplified. Recent studies implicate the host immune response as a major modality of SVD pathogenesis, manifested by a combination of processes phenocopying the long‐term transplant rejection, atherosclerosis, and calcification of native aortic valves. In this review, we summarize and critically analyze relevant studies on (1) SVD triggers and pathogenesis, (2) current approaches to protect BHVs from calcification, (3) obtaining low immunogenic BHV tissue from genetically modified animals, and (4) potential strategies for SVD prevention in the clinical setting.

Invasive coronary angiography remains the gold standard for diagnosing coronary artery disease, which may be complicated by both, patient-specific anatomy and image quality. Deep learning techniques aimed at detecting coronary artery stenoses may facilitate the diagnosis. However, previous studies have failed to achieve superior accuracy and performance for real-time labeling. Our study is aimed at confirming the feasibility of real-time coronary artery stenosis detection using deep learning methods. To reach this goal we trained and tested eight promising detectors based on different neural network architectures (MobileNet, ResNet-50, ResNet-101, Inception ResNet, NASNet) using clinical angiography data of 100 patients. Three neural networks have demonstrated superior results. The network based on Faster-RCNN Inception ResNet V2 is the most accurate and it achieved the mean Average Precision of 0.95, F1-score 0.96 and the slowest prediction rate of 3 fps on the validation subset. The relatively lightweight SSD MobileNet V2 network proved itself as the fastest one with a low mAP of 0.83, F1-score of 0.80 and a mean prediction rate of 38 fps. The model based on RFCN ResNet-101 V2 has demonstrated an optimal accuracy-to-speed ratio. Its mAP makes up 0.94, F1-score 0.96 while the prediction speed is 10 fps. The resultant performance-accuracy balance of the modern neural networks has confirmed the feasibility of real-time coronary artery stenosis detection supporting the decision-making process of the Heart Team interpreting coronary angiography findings.

The development of a novel artificial heart valve with outstanding durability and safety has remained a challenge since the first mechanical heart valve entered the market 65 years ago. Recent progress in high-molecular compounds opened new horizons in overcoming major drawbacks of mechanical and tissue heart valves (dysfunction and failure, tissue degradation, calcification, high immunogenic potential, and high risk of thrombosis), providing new insights into the development of an ideal artificial heart valve. Polymeric heart valves can best mimic the tissue-level mechanical behavior of the native valves. This review summarizes the evolution of polymeric heart valves and the state-of-the-art approaches to their development, fabrication, and manufacturing. The review discusses the biocompatibility and durability testing of previously investigated polymeric materials and presents the most recent developments, including the first human clinical trials of LifePolymer. New promising functional polymers, nanocomposite biomaterials, and valve designs are discussed in terms of their potential application in the development of an ideal polymeric heart valve. The superiority and inferiority of nanocomposite and hybrid materials to non-modified polymers are reported. The review proposes several concepts potentially suitable to address the above-mentioned challenges arising in the R&D of polymeric heart valves from the properties, structure, and surface of polymeric materials. Additive manufacturing, nanotechnology, anisotropy control, machine learning, and advanced modeling tools have given the green light to set new directions for polymeric heart valves.

Polymeric heart valves seem to be an attractive alternative to mechanical and biological prostheses as they are more durable, due to the superior properties of novel polymers, and have the biocompatibility and hemodynamics comparable to tissue substitutes. This study reports a comprehensive assessment of a nanocomposite based on the functionalised graphene oxide and poly(carbonate-urea)urethane with the trade name “Hastalex” in comparison with GORE-TEX, a commercial polymer routinely used for cardiovascular medical devices. Experimental data have proved that GORE-TEX has a 2.5-fold (longitudinal direction) and 3.5-fold (transverse direction) lower ultimate tensile strength in comparison with Hastalex (p < 0.05). The contact angles of Hastalex surfaces (85.2 ± 1.1°) significantly (p < 0.05) are lower than those of GORE-TEX (127.1 ± 6.8°). The highest number of viable cells Ea.hy 926 is on the Hastalex surface exceeding 7.5-fold when compared with the GORE-TEX surface (p < 0.001). The platelet deformation index for GORE-TEX is 2-fold higher than that of Hastalex polymer (p < 0.05). Calcium content is greater for GORE-TEX (8.4 mg/g) in comparison with Hastalex (0.55 mg/g). The results of this study have proven that Hastalex meets the main standards required for manufacturing artificial heart valves and has superior mechanical, hemocompatibility and calcific resistance properties in comparison with GORE-TEX.

Atherosclerosis, calcific aortic valve disease (CAVD), and bioprosthetic heart valve degeneration (alternatively termed structural valve deterioration, SVD) represent three diseases affecting distinct components of the circulatory system and their substitutes, yet sharing multiple risk factors and commonly leading to the extraskeletal calcification. Whereas the histopathology of the mentioned disorders is well-described, their ultrastructural pathology is largely obscure due to the lack of appropriate investigation techniques. Employing an original method for sample preparation and the electron microscopy visualisation of calcified cardiovascular tissues, here we revisited the ultrastructural features of lipid retention, macrophage infiltration, intraplaque/intraleaflet haemorrhage, and calcification which are common or unique for the indicated types of cardiovascular disease. Atherosclerotic plaques were notable for the massive accumulation of lipids in the extracellular matrix (ECM), abundant macrophage content, and pronounced neovascularisation associated with blood leakage and calcium deposition. In contrast, CAVD and SVD generally did not require vasculo- or angiogenesis to occur, instead relying on fatigue-induced ECM degradation and the concurrent migration of immune cells. Unlike native tissues, bioprosthetic heart valves contained numerous specialised macrophages and were not capable of the regeneration that underscores ECM integrity as a pivotal factor for SVD prevention. While atherosclerosis, CAVD, and SVD show similar pathogenesis patterns, these disorders demonstrate considerable ultrastructural differences.